|
on Computational Economics |
|
Issue of 2015‒12‒08
three papers chosen by |
| By: | Josep-Maria Salanova Grau (Hellenic Institute or Transport - Center of Research and Technologie Hellas); Jesus Gonzalez-Feliu (PIESO-ENSMSE - Département Performance Industrielle et Environnementale des Systèmes et des Organisations - Mines Saint-Étienne MSE - École des Mines de Saint-Étienne - Institut Mines-Télécom - Institut Henri Fayol, EVS - UMR 5600 Environnement Ville Société - ENS Lyon - École normale supérieure - Lyon - UL2 - Université Lumière - Lyon 2 - Université Jean Moulin - Lyon III - Université Jean Monnet - Saint-Etienne - École Nationale des Travaux Publics de l'État [ENTPE] - Ecole Nationale Supérieure des Mines de Saint-Etienne - ENSAL - Ecole nationale supérieure d'architecture de Lyon - CNRS - Centre National de la Recherche Scientifique) |
| Abstract: | This paper proposes a comparison between two fast heuristic algorithms to solve a multi-carrier 2E-VRP in city logistics, under realistic conditions. We propose a cluster-first route second algorithm to compare the performance of two route construction and post-optimization algorithms on real-size test cases. The clustering phase is made by a seep algorithm, which defines the number of used vehicles and assigns a set of customers to it. Then, for each cluster, which represents a vehicle, we build a min-cost route by the two following methods. The first is a semi-greedy algorithm. The second is a genetic algorithm that includes post-optimization at the level of each route. In this work we make the route construction and post-optimization without any possible exchange of the routes to guaranty a pertinent comparison between both algorithms. After presenting both approaches, we apply them, first to classical 2E-CVRP instances to state on the algorithm capabilities, then on real-size instances to compare them. Computational results are presented and discussed. Finally, practical implications are addressed. |
| Keywords: | multi-carrier two-echelon vehicle routing,city logistics,cross-docking,heuristics comparison,route construction |
| Date: | 2015 |
| URL: | http://d.repec.org/n?u=RePEc:hal:journl:halshs-01176134&r=cmp |
| By: | Andrea Carriero (Queen Mary University of London); Todd E. Clark (Federal Reserve Bank of Cleveland); Massimiliano Marcellino (Bocconi University, IGIER and CEPR) |
| Abstract: | We propose a new algorithm which allows easy estimation of Vector Autoregressions (VARs) featuring asymmetric priors and time varying volatilities, even when the cross sectional dimension of the system <i>N</i> is particularly large. The algorithm is based on a simple triangularisation which allows to simulate the conditional mean coefficients of the VAR by drawing them equation by equation. This strategy reduces the computational complexity by a factor of <i>N<sup>2</sup></i> with respect to the existing algorithms routinely used in the literature and by practitioners. Importantly, this new algorithm can be easily obtained by modifying just one of the steps of the existing algorithms. We illustrate the benefits of the algorithm with numerical and empirical applications. |
| Keywords: | Bayesian VARs, Stochastic volatility, Large datasets, Forecasting, Impulse response functions |
| JEL: | C11 C13 C33 C53 |
| Date: | 2015–11 |
| URL: | http://d.repec.org/n?u=RePEc:qmw:qmwecw:wp759&r=cmp |
| By: | Victor Kummritz (IHEID, The Graduate Institute of International and Development Studies, Geneva); Bastiaan Quast (IHEID, The Graduate Institute of International and Development Studies, Geneva) |
| Abstract: | Global Value Chains have become a central unit of analysis in research on international trade. However, the complex matrix transformations at the basis of most Value Chain indicators still constitute a significant entry barrier to the field. The R package decompr solves this problem by implementing the algorithms for the analysis of Global Value Chains as R procedures, thereby simplifying the decomposition process. Two methods for gross export flow decomposition using Inter-Country Input-Output tables are provided. The first method concerns a decomposition based on the classical Leontief (1936) insight. It derives the value added origins of an industry's exports by source country and source industry, using easily available gross trade data. The second method is the Wang-Wei-Zhu algorithm, which splits bilateral gross exports into 16 value added components. These components can broadly be divided into domestic and foreign value added in exports. Using the results of the two decompositions, decompr provides a set of Global Value Chain indicators, such as the now standard Vertical Specialisation ratio. This article summarises the methodology of the algorithms, describes the format of the input and output data, and exemplifies the usefulness of the two methods on the basis of a simple example data set. |
| Keywords: | Global Value Chains, Trade in Value Added, Export Decomposition |
| JEL: | E01 F13 F14 F23 L14 |
| Date: | 2015–01–17 |
| URL: | http://d.repec.org/n?u=RePEc:gii:cteiwp:ctei-2015-01&r=cmp |